{"id":"W4389524414","doi":"10.18653/v1/2023.emnlp-demo.12","title":"Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face","year":2023,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Face (sociological concept); Computer science; Zhàng; Linguistics; History; China; Philosophy; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002453544,0.00008550732,0.000101613,0.0000857119,0.0000656339,0.0001377573,0.0002061751,0.00002413948,0.000008875064],"category_scores_gemma":[0.00001064755,0.00006324014,0.000009350133,0.000253587,0.00002483361,0.0002308388,0.0003501826,0.00008056153,0.00002581391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000636407,"about_ca_system_score_gemma":0.0000249429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006782187,"about_ca_topic_score_gemma":0.00001623079,"domain_scores_codex":[0.9991777,0.0000178041,0.00008826016,0.0003150056,0.0001748009,0.0002264422],"domain_scores_gemma":[0.9995202,0.00007817494,0.00001279647,0.0002870233,0.00002163418,0.00008017541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002758124,0.0000441972,0.06145282,0.0003145703,0.0001283346,0.0002808399,0.02403743,0.09120744,0.005717987,0.3256913,0.002412106,0.4886854],"study_design_scores_gemma":[0.0002801121,0.00005544873,0.02624313,0.00002305613,0.000001999776,0.0000454887,0.0003232148,0.9689742,0.001470582,0.0003090469,0.002079317,0.0001944282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5354591,0.00004193199,0.4604878,0.001923881,0.00005526104,0.00007231046,2.97062e-7,0.0003849849,0.001574437],"genre_scores_gemma":[0.943933,0.00003971778,0.0528758,0.00009901793,0.00003243304,0.000005305696,3.745105e-7,0.000008561129,0.003005816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8777667,"threshold_uncertainty_score":0.2578858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03053542169169943,"score_gpt":0.2614568801368183,"score_spread":0.2309214584451189,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}